Abstract: The present invention is directed to systems and methods for displaying and contributing to a database of genomic information in a notebook-like format, with emphasis on establishing and viewing relationships between data points in the database. The present invention features a server containing the database of genomic information and a computing device communicatively coupled to the database. The computing device may comprise a Note Input Module for allowing the user to input a note into the database of genomic information. The note may be associated with a first data point and connect it to one or more second data points. The computing device may further comprise a Note Association Module for adding to the list of associated data points of a pre-existing note. The computing device may further comprise a Browsing Module for allowing a user to search the database of genomic information for data points and notes.

Abstract: The present invention is directed to systems and methods for displaying and contributing to a database of genomic information in a notebook-like format, with emphasis on establishing and viewing relationships between data points in the database. The present invention features a server containing the database of genomic information and a computing device communicatively coupled to the database. The computing device may comprise a Note Input Module for allowing the user to input a note into the database of genomic information. The note may be associated with a first data point and connect it to one or more second data points. The computing device may further comprise a Note Association Module for adding to the list of associated data points of a pre-existing note. The computing device may further comprise a Browsing Module for allowing a user to search the database of genomic information for data points and notes.

Abstract: A method for efficiently processing and storing large data sets associated with a multi-stage bioinformatics analysis of genomic data is disclosed. The present method increases the efficiency of the electronic storage of these large data sets by automatically deleting or compressing intermediate data or a portion of output data and compressing input data, where both deletion and compression are based on predetermined characteristics of said data. When necessary, such data can be recovered using generated metadata associated with the data. Doing so, not only improves the storage efficiency of massively large genomic datasets, but also allows for the consistent reproduction of output data with the re-processing of intermediate data based on information stored in metadata.

Abstract: A method for efficiently processing and storing large data sets associated with a multi-stage bioinformatics analysis of genomic data is disclosed. The present method increases the efficiency of the electronic storage of these large data sets by automatically deleting or compressing intermediate data or a portion of output data and compressing input data, where both deletion and compression are based on predetermined characteristics of said data. When necessary, such data can be recovered using generated metadata associated with the data. Doing so, not only improves the storage efficiency of massively large genomic datasets, but also allows for the consistent reproduction of output data with the re-processing of intermediate data based on information stored in metadata.

Abstract: A method for efficiently processing and storing large data sets associated with a multi-stage bioinformatics analysis of genomic data is disclosed. The present method increases the efficiency of the electronic storage of these large data sets by automatically deleting or compressing intermediate data or a portion of output data and compressing input data, where both deletion and compression are based on predetermined characteristics of said data. When necessary, such data can be recovered using generated metadata associated with the data. Doing so, not only improves the storage efficiency of massively large genomic datasets, but also allows for the consistent reproduction of output data with the re-processing of intermediate data based on information stored in metadata.